Large scale commercial manufacturing and refining processes typically use process controllers to control the operation of one or more process control devices such as valves, based on feedback from one or more sensors, such as flow, temperature or other types of sensors. Each set of such controller, valve and sensor devices forms what is generally referred to as a process control loop. Furthermore, each valve or other device may, in turn, include an inner loop wherein, for example, a valve positioner controls a valve actuator to move a control element, such as a valve plug, in response to a control signal and obtains feedback from a sensor, such as a position sensor, to control movement of the valve plug. This inner loop is sometimes called a servo loop. In any event, the control element of a process control device may move in response to changing fluid pressure on a spring biased diaphragm or in response to the rotation of a shaft, each of which may be caused by a change in the command signal. In one standard valve mechanism, a command signal with a magnitude varying in the range of 4 to 20 mA (milliamperes) causes a positioner to alter the amount of fluid and thus, the fluid pressure, within a pressure chamber in proportion to the magnitude of the command signal. Changing fluid pressure in the pressure chamber causes a diaphragm to move against a bias spring which, in turn, causes movement of a valve plug.
Process control devices usually develop or produce a feedback signal, indicative of the response of the device to the command signal, and provide this feedback signal (or response indication) to the process controller or to the valve actuator for use in controlling the process or the valve. For example, valve mechanisms typically produce a feedback signal indicative of the position (e.g., travel) of a valve plug, the pressure within a fluid chamber of the valve or the value of some other phenomena related to the actual position of the valve plug.
While a process controller generally uses these feedback signals, along with other signals, as inputs to a highly tuned, centralized control algorithm that effects overall control of a process, it has been discovered that poor control loop performance may still be caused by poor operating conditions of the individual control devices connected within the control loop including, for example, instabilities within the process control loop. A system experiences an “instability” when it cannot reach an equilibrium point during operation. Plant personnel often refer to these instabilities as cycling, hunting, or swinging which is in contrast with normal operation in which the system reaches an equilibrium point or “lines-out.”
In many cases, problems associated with one or more of the individual process control devices cannot be tuned out of the control loop by the process controller and, as a result, the poorly performing control loops are placed in manual or are detuned to the point where they are effectively in manual. In some cases, plant personnel can track down individual loops that are cycling and will detune the associated controller or place the faulty loop into manual. If the system settles down, they know that it is a tuning problem, not a hardware problem. In a similar fashion, if the process has well known, fast dynamics (such as a flow loop), operators will correlate the controller output with the process variable. If the output of the controller is a triangle wave and the process variable is a square wave, they will often conclude that the control valve is sticking. These ad-hoc procedures are used by many plant operators, but include several limitations. For example, the first procedure requires the operator to put the system into manual, which may not be allowed, especially on runaway processes. The second procedure is good for identifying limit cycles induced by the process control loop but is not capable of tracking down instabilities in the servo loop. Moreover, correlation between a command signal and a process variable is not always straightforward due to complications such as integrating process dynamics, nonlinear process dynamics, cross-coupled process dynamics, and process disturbances. Instabilities in the servo loop can be particularly difficult to discern because plant personnel do not have access to the internal state variables of a control valve. Additional problems arise when instabilities are influenced by the process fluid, as is the case with negative gradients. In these situations, a valve can oscillate when in service, but becomes well behaved when it is taken off line.
Poor control loop performance can usually be overcome by monitoring the operational condition or the “health” of each of the process control devices connected within the loop, or at least the most critical process control devices connected within the loop, and repairing or replacing the poorly performing process control devices. The health of a process control device can be determined by measuring one or more parameters associated with the process control device and determining if the one or more parameters is outside of an acceptable range. One of the problems that may be monitored is the detection of instabilities in a process loop or a control device. Such instabilities may be the result of, for example, limit cycles which cause the loop to oscillate.
In particular, the term limit cycle generally refers to undesirable cyclical movements of a moveable element within a process control device, such as a sliding stem valve. There are many causes of limit cycles including, for example, external forces, friction and mechanical anomalies. External forces, such as buffeting or jet streams or other forces which place a negative gradient on, for example, a valve plug, may cause movement of the element, which is then compensated for by the control mechanism either within or outside of the servo loop. Friction, for example, increased friction caused by side loading on the moveable element, may prevent initial movement of the element thereby causing the control mechanism to increase the pressure on the moveable element. This increased pressure causes overshoot and, thereby, initiates cyclical movement of the element. Mechanical or device anomalies may include interactions between actuator pneumatics and those of supporting equipment such as air supply regulators, volume boosters or quick-release valves or other anomalies involving the supporting equipment. In summary, limit cycles may be caused by a process control loop itself, by external forces, valve accessories, friction, etc.
In the past, it was not easy to determine the source or cause of an instablity within a process control loop without having a technician review and diagnose the system, which could be time consuming and costly. In some cases these persons had to remove a process control device from a control loop to bench test the device or, alternatively, the control loops themselves were provided with bypass valves and redundant process control devices to make it possible to bypass a particular process control device to thereby test a device while the process is operating. Alternatively, operators have had to wait until a process is halted or is undergoing a scheduled shut-down to test the individual process control devices within the process which might be the source of an instability. Each of these options is time consuming, expensive, and only provides intermittent determination of instabilities in a system. Still further, none of these methods is particularly suited to determine the source or cause of an instability while the process is operating on-line, i.e., without disturbing or shutting the process down.
There have been some attempts to collect data from a process control device on-line and to obtain an indication of characteristics of a device therefrom. For example, U.S. Pat. No. 5,687,098 to Grumstrup et al. discloses a system that collects device data and constructs and displays the response characteristic of the device. Likewise, application Ser. No. 08/939,364 filed Sep. 29, 1997 entitled “Method of and Apparatus for Nonobtrusively Obtaining On-Line Measurements of a Process Control Device Parameter,” upon which this application relies for priority purposes, discloses a system that collects device data on-line and uses this data to directly calculate certain device parameters, such as dead band, dead time, etc. The disclosure of this application specifically related to an apparatus and method for obtaining on-line measurements of a process control device parameters (i.e., the disclosure related to FIGS. 1–3) is hereby expressly incorporated by reference herein. Furthermore, the disclosure of U.S. patent application Ser. No. 09/370,474 filed Aug. 9, 1999 entitled “Statistical Determination of Estimates of Process Control Loop Parameters” is also hereby expressly incorporated by reference herein. However, none of the known prior art methods or systems determines the causes of instabilities within a process control system, especially when the process control system is operating on-line.